In 2021, more than 1.9 million people in the United States were estimated to be diagnosed with cancer, and that number continues to increase yearly. Medical research is critical in prolonging survival and improving the quantity and quality of life of patients. Cancer research is one of the most heavily invested areas, with more than $5 billion spent annually in the United States on exploring and developing new therapeutic options.
A significant element of cancer research relies on accurate available patient data, but most of it is limited in quantity and scope. This information is currently obtained from electronic medical records, pharmaceutical laboratories, and clinical trials, limiting analyses to smaller cohorts of patients, significantly affecting the obtained end results. These types of controlled environments can produce synthetic outcomes and data that may not always be reflective of real-life situations.
An important consideration is that most research in cancer care focuses on the disease, rather than the individual patients themselves. When the primary goal is to shrink tumors and kill cancer cells, research and collected data tend to favor the view of clinicians, and valuable insights provided by patients may be missed. For data to be more beneficial, they must not be limited solely to patients’ clinical response and toxicity experiences but should also take into consideration all facets of a patient’s life—including demographics; financial status; as well as social, psychological, emotional, and logistical factors.
Daniel Vorobiof, MD
Irad Deutsch
Only through the aggregation of such comprehensive data, researchers might uncover new patterns in cancer diagnosis, treatment, and prognosis, which will contribute to our broader understanding and management of the disease as a whole and of patients with it.
Engagement Within Patients’ Communities
Due to the increase in patients’ online communities (social and professional), it has become possible to track full cancer journeys within a large population. Online platforms allow patients to provide information specific to their condition and connect with others in similar clinical situations while at the same time tracking their disease journey. Members of online communities, while posting anonymously, tend to be more forthcoming regarding a variety of personal aspects of their journey, leading to the availability of comprehensive data while keeping individual privacies.
To maximize data usability, a large population is needed to enable wide demographics. For that, high patient engagement is essential, becoming a continuous challenge for those online forums and applications. How to achieve this goal is by ensuring the platform provides true value for the users. If an application requests too much time and dedication from patients—for example, asking them to regularly track symptoms and fill out questionnaires—patients will stop using them, resulting in few to no reliable data becoming readily available.
For the sake of retaining members and keeping them engaged, online patient communities need to provide different tools and features, encouraging engagement from the very beginning. Many different topics include medically verified content, networking facilities with other patients, contact with medical professionals and allied professions, and other useful tools available for those patients diagnosed with a variety of chronic diseases.
For example, a way to track and manage symptoms and side effects and a storage facility of medical files are illustrations of features that may keep patients engaged. This practical and manageable tool will encourage patients to use the applications and platforms multiple times a day, ultimately generating large amounts of data beyond their treatment, providing insight into the holistic and comprehensive patient journey.
Tracking Data Input
The current knowledge and regular availability of artificial intelligence (AI) and machine learning have allowed researchers to evaluate large data volumes that can generate meaningful insights in a more effective and efficient way. These revolutionary technologies are also able to detect subjective patient information (for example, concerns and sentiments) that is not usually captured by electronic medical records. In addition, algorithms might detect a variety of different clinical data points such as disease symptoms or those related to drug efficacy and the onset of side effects while also looking for other environmental or lifestyle changes that may affect a patient’s personal experience.
Both AI and machine learning can connect the dots between most observed data points, discovering new connections or patterns. In that way, and by observing a specific causality, we can gain deep insights into many currently neglected aspects of cancer care. Most of this chain of events is, in fact, the patient’s own journey, and important discoveries can be made through observing those large numbers of patients.
It is well known that cancers are not always caused by a single genetic or familial defect or mutation but mostly by the accumulation of multifactorial triggers and environmental changes. The ability to identify those factors and track health determinants through patient online communities provides a preventive set of tools to anticipate the possible risk of developing a cancer and the measures to be taken to minimize them.
Real-World Data and Real-World Evidence in Health-Care Decisions
In recent years, different members of the health community (eg, pharma, treating physicians, insurance companies) are using information originated by real-world data and real-world evidence, which are playing an increasing role in many health-care decisions. They are used by the U.S. Food and Drug Administration for several reasons: to monitor postmarketing safety; to make regulatory decisions; to support coverage selection by the health-care community; to help physicians make important therapeutic choices; to develop guidelines for use in clinical practice; and to aid investigators in developing large observational clinical trials that are innovative and relevant to a large number of patients with cancer.
Data must not be limited solely to a patient’s clinical response and toxicity experiences but should also take into consideration all facets of a patient’s life.— Daniel Vorobiof, MD, and Irad Deutsch
Tweet this quote
Shaping the Future of Cancer Care
As previously mentioned, data that are aggregated and analyzed from online patient communities with the help of AI and machine learning are ripe with various opportunities for researchers. The abundance of information available, highlighting so many aspects of the unique patient journey, provides new, real-world insight and understanding, which largely have remained hidden until now. Through the analysis of these data, researchers may gain new perspectives on a variety of important facets, including the real cost of illness (financial toxicity), length and scheduling of treatment plans, benefits of alternative/complementary treatments in conjunction with a medical regimen, and management of uncommon side effects.
Such insights have already provided the backbone of diverse studies, including the effect of COVID-19 in patients with cancer, the extent of financial toxicity in patients with cancer receiving a variety of treatments, and how the diagnosis of breast cancer might affect the sex life of patients and their partners. Wider sharing of this knowledge can significantly improve patients’ care and quality of life. With the amount of data available and growing, we can anticipate that many additional studies are already being planned and in the pipeline.
Involvement of online patient communities is an integral tool for improving the standards of the traditional approach to cancer care and research. By going beyond treatment to consider individual patients’ journeys, it is possible to uncover hidden patterns that ultimately may improve quality of life for individual patients and cancer populations.
DISCLOSURE: An editorial board advisor for The ASCO Post, Dr. Vorobiof is Medical Director of Belong.Life, a global tech provider of high-engagement patient communities and care platforms for people with cancer and other illnesses worldwide. Mr. Deutsch is Cofounder and Chief Technology Officer of Belong.Life.
